Tools: match keyword hints on word boundaries

`get_tools_for_query` force-includes whole tool families when the query
mentions an intent keyword, but matched with a raw substring test
(`kw in ql`). Short hints therefore fired inside unrelated words, bloating
the tool set with irrelevant tools:

  - "fix" matched "prefix"      -> document tools
  - "line" matched "deadline"/"online" -> document tools
  - "serve" matched "observe"/"reserve" -> cookbook serve tools
  - "reply" matched "replying"  -> all email tools
  - "unread" matched "unreadable" -> all email tools

Match each keyword on word boundaries instead
(`re.search(rf"\b{re.escape(kw)}\b", ql)`), the same fix already applied to
the keyword matcher in topic_analyzer.py. Genuine intent keywords
("reply to this email", "edit the document", "serve the model") still match.

This only removes substring-inside-a-word matches; it does not change whole
-word matches (so e.g. an unrelated whole word like "tell" is a separate
keyword-choice question, left untouched here).

Checks: python -m pytest tests/test_tool_index_keyword_boundaries.py (4 passed;
3 of them fail on the pre-fix substring code), python -m py_compile
src/tool_index.py, git diff --check.

src/tool_index.py

@@ -431,10 +431,14 @@ class ToolIndex:
         base = set(always_include or ALWAYS_AVAILABLE)
         retrieved = self.retrieve(query, k=k)
         base.update(retrieved)
-        # Keyword-based force-include for common intents
+        # Keyword-based force-include for common intents. Match on word
+        # boundaries, not raw substrings, so short hints like "fix", "line",
+        # "serve", "reply" or "unread" don't fire inside unrelated words
+        # ("prefix", "deadline"/"online", "observe"/"reserve", "replying",
+        # "unreadable"). Same word-boundary matching used in topic_analyzer.
         ql = query.lower()
         for keywords, tools in self._KEYWORD_HINTS.items():
-            if any(kw in ql for kw in keywords):
+            if any(re.search(rf"\b{re.escape(kw)}\b", ql) for kw in keywords):
                 base.update(tools)
         # Structural scheduling-intent detection — typo-resilient (the literal
         # keyword "every day" misses "every dya"). Catches "every <word>",